Determining capability of an on-line sensor

ABSTRACT

Devices, systems and methods for determining capabilities of an on-line sensor are disclosed. The exemplary method may comprise the following acts. The method may generate an image of a sample texture with known characteristics. The method may transfer the image to an on-line sensor. The method may also analyze data generated by the on-line sensor to determine measured characteristics. The method may compare the measured characteristics to the known characteristics.

FIELD OF THE INVENTION

The present invention relates generally to determining capabilities of asensor, and more particularly to determining quality characteristics ofan on-line sensor in a manufacturing process.

BACKGROUND OF THE INVENTION

Manufacturers may need to monitor and control the product quality usingon-line sensors during processing of the product. An on-line sensor maybe used to determine characteristics of the product texture during theprocessing of the product. The on-line sensor may receive a beam oflight reflected off the surface of the product or transmitted throughthe product. The on-line sensor may then analyze the reflected ortransmitted light and the original beam of light to determine qualitiesof the product texture. The product may be, for example, paper or asheet of material.

The manufacturing environment may produce conditions that may affect theaccuracy of the on-line sensor. For example, vibrations of componentsused in the processing of the product, temperature variations, and/ordust produced during processing of the product may reduce the accuracyof the on-line sensor.

In order to verify the accuracy of on-line sensors, a sample of theproduct may be measured in a laboratory. In a controlled laboratoryenvironment, laboratory sensors may be used to attempt to provide a moreaccurate measurement of the sample. The sample is also tested using theon-line sensor. The results of the laboratory sensor are compared withthe on-line sensor to identify the accuracy and/or capabilities of theon-line sensor.

However, an undesirable situation may result when the on-line sensor hashigher capability than the laboratory sensor, which then may lead topoor correlation between the sensors. The results may then beinterpreted as the fault of the on-line sensor. Accordingly, anefficient and effective device, method, and system are needed forproviding more accurate comparisons between the true qualities of asample texture and measured qualities of an on-line sensor. In addition,the device, system and method may need to provide a more accuratecomparison between the true qualities of a sample texture, laboratorymeasured qualities of the sample texture and the measured qualities byan on-line sensor of the sample texture.

SUMMARY OF THE INVENTION

It is, therefore, an object of the present invention to provide devices,systems, and methods for determining capabilities of an on-line sensor.According to an exemplary embodiment of the present invention, themethod may generate an image of a sample texture with knowncharacteristics. The exemplary method may transfer the image to anon-line sensor. The exemplary method may analyze data generated by theon-line sensor to determine measured characteristics and compare themeasured characteristics to the known characteristics.

According to an exemplary embodiment of the present invention, thedevice may incorporate the following embodiments. In one embodiment,generating an image of a sample texture may involve a computer algorithmgenerating a two-dimensional matrix of a disordered medium. The act ofgenerating an image of a sample texture may also involve generating atwo-dimensional matrix of a disordered medium from an image of a knowntextured surface. In another embodiment, transferring the image mayinvolve printing an image copy and presenting the image copy to theon-line sensor. In an additional embodiment, transferring the image mayinvolve displaying an image copy and presenting the displayed image copyto the on-line sensor. In yet another embodiment, transferring the imagemay involve displaying an image copy and reflecting the displayed imagecopy onto the on-line sensor. In another embodiment, the exemplarymethod may further involve transferring the image to a laboratorysensor; analyzing data generated by the laboratory sensor to determinemeasured characteristics; and comparing the known characteristics to themeasured characteristics of the on-line sensor and to the measuredcharacteristics of the laboratory sensor. In another embodiment,comparing the known characteristics may involve generating amathematical formula of a cross-correlation between the measuredcharacteristics and the known characteristics.

BRIEF DESCRIPTION OF THE DRAWINGS

The above and other objectives and advantages of the present inventionwill be apparent upon consideration of the following detaileddescription, taken in conjunction with the accompanying drawings, inwhich like reference numbers refer to like parts throughout, and inwhich:

FIG. 1 illustrates images of computer simulated sample textures printedon a transparent medium.

FIG. 2 is a generalized schematic of a sampling device used to implementa first exemplary sampling embodiment of the present invention.

FIG. 3 is a generalized schematic of a sampling device used to implementa second exemplary sampling embodiment of the present invention.

FIG. 4 is a generalized schematic of a sampling device used to implementa third exemplary sampling embodiment of the present invention.

FIG. 5 is a flow chart illustrating a first exemplary sampling methodembodiment of the present invention.

FIG. 6 is a flow chart illustrating a second exemplary sampling methodembodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION

The present invention provides a device, system, and method to monitorand control the quality of on-line sensors measurements. An on-linesensor may be used to determine characteristics of a product's textureduring the processing of the product. The product may be, for example,paper, woven fabric, or a minor periodic textures in otherwisedisordered media, for example, a wire mark in paper. The on-line sensormay utilize a photo detector to receive a beam of light reflected offthe product or transmitted through the product. The photo detectorconverts the received light into an electrical signal. The electricalsignal is analyzed to determine characteristics of the texture.

The present invention generates a sample texture with knowncharacteristics. The sample texture may be generated by a computerproducing a two-dimensional matrix with mathematical algorithms. Thesample texture may be printed on a medium and placed in an inspectionarea of the on-line sensor or the sample texture may be reflected ontothe on-line sensor. The on-line sensor determines the characteristics ofthe sample texture. The characteristics generated by the on-line sensorare compared to the known characteristics of the sample texture todetermine the quality of the on-line sensor.

The computer-generated sample texture may provide specific propertiesand reference points for the on-line sensor measurement to be assessed.The capability of the on-line sensor device can be quantified withoutthe disadvantages related to material samples supplied through theproduction process. The computer-generated sample texture may alsoprovide a calibration between differently designed measurement devices.For example, measurement sensors designed and built by differentmanufacturers may be analyzed with respect to one another. In the caseof low correlation between the measurement sensors, the more accurateone may objectively be identified. In addition, the base calibration(factory calibration) and inter-sensor calibration can be made moreaccurate using the invention.

Referring to FIG. 1, five images OF1-OF5 of computer simulated sampletextures and a sample including a grayscale step target OF6 are shown.The five images OF1-OF5 of the sample texture are printed on atransparent medium with an inkjet printer using the methods and devicesdescribed herein.

Referring to FIG. 2, a sampling device 200 according to a firstexemplary sampling embodiment is used to evaluate a sensor. The samplingdevice 200 may be used to determine the capabilities of an on-linesensor 202. The user of the sampling device 200 may select and set oneor more simulation parameters 204 for a simulated sample texture. Thegeneration of the texture is controlled using the parameters in order toachieve desired properties, e.g., mimicking real-life samples in somemanufacturing process operating point. The simulation parameters 204 maybe properties of a typical texture examined by sensors 202. Thesimulation parameters 204 are fed into an analyzing device 206. Theanalyzing device 206 may feed the simulation parameters 204 into aqualitative comparator 208 and a quantitative comparator 210. Theanalysis performed by the qualitative comparator 208 and thequantitative comparator 210 is discussed later herein. The one or moresimulation parameters 204 are also fed into a computer algorithm 212.

The computer algorithm 212 may generate a two-dimensional array withstatistical properties typical of a medium being analyzed based on thesimulation parameters 204. The computer algorithm 212 may be astatistical simulation building the image from basic constituents of themedium, for example, simulation parameters 204 of the fibers or otherproduct components. The computer algorithm 212 may also be based onmathematical formulas, for example, fractals that produce statisticalproperties similar to the disordered properties typical of the medium.The computer algorithm 212 may also use a combination of both simulationand mathematical formulas. The two-dimensional array may provide anon-homogeneous medium with or without repeatable structures.

An image 214 of the sample texture may be generated from thetwo-dimensional array. A printing device 216 may be used to produce theimage 214 on or into a homogeneous medium. The homogeneous medium maybe, for example, but not limited to, film, transparency, semi-opaque ornon-opaque printing medium. In another example, a non-homogeneous mediummay be used. According to this example, the simulation parameters 204may be designed to take into account the non-homogeneous structure ofthe medium. The printing device 216 used to print may be a variety ofdevices known to an individual skilled in the art. In yet anotherexample, the printing device 216 may be etched or machined on to amedium. The image 214 would provide a surface topography of the sampletexture, for example, the fiber orientation of a sample. The printingdevice 216 may be selected based on the medium selected to display theimage 214.

The image 214 on the medium is placed in the detection area of theon-line sensor 202. The on-line sensor 202 scans the image 214 displayedon the homogeneous medium. The on-line sensor 202 may scan the sampleusing a variety of radiation sources, for example, light, x-ray, andelectron beam. The conditions used to scan the image 214 on thehomogeneous medium may be designed to be similar to the actualconditions seen during normal operation of the on-line sensor 202. Forexample, the image 214 may be displayed in front of the on-line sensor202 using the same conveying device used during normal operation.

The on-line sensor 202 or a component of the on-line sensor may separatethe image 214 viewed by the on-line sensor 202 down into measuredparameters 218. These measured parameters 218, may be, for example, butnot limited to the reflected or transmitted illumination detected by theon-line sensor 202 or the variability of illumination detected by theon-line sensor 202. The measured parameters 218 are fed into theanalyzing device 206. The analyzing device 206 may feed the measuredparameters into the qualitative comparator 208 and the quantitativecomparator 210. The qualitative comparator 208 and the quantitativecomparator 210 compare the simulation parameters 204 to the measuredparameters 218. The analyzing device 206 may provide an accuratecomparison of the on-line sensor 202 to other sensors. Additionalmanipulation of the parameters 204, 218 may be provided to produce abetter understanding of the accuracy of the on-line sensor 202. Forexample, the quantitative device 210 may be used to provide across-correlation between the simulation parameters 204 and the measuredparameters 218. In addition, mathematical formulas may be generated todepict and/or predict the error of the on-line sensor 202.

The systems and methods used by the computer algorithms 212 andanalyzing device 206 on the simulation parameters 204 and measuredparameters 218 may be incorporated in software used with a computer orother suitable operating device. Architecturally in terms of hardware,the simulation parameters 204, computer algorithms 212, measuredparameters 218, and analyzing device 206 may utilize a processor,memory, and one or more input and output interface devices. The variousinterface devices may have additional elements, which are omitted forsimplicity, such as controllers, buffers (caches), drivers, repeaters,and receivers, to enable communications. As previously discussed theimage 214 produced by the computer algorithm 212 may be supplied to aprinting device 216 coupled to an interface device. The software mayalso provide a Graphic User Interface (GUI) to allow the administratoror user to enter, edit, view and/or store the image 214 as well assimulation parameters 204. Similarly, the analyzing device 206 may alsouse a GUI to allow the administrator to analyze, edit, view and/or storedata associated with the comparison of the simulation parameters 204 andmeasured parameters 218.

Referring to FIG. 3, a sampling device 300 according to a secondexemplary sampling embodiment is used to evaluate a sensor. The samplingdevice 300 may be used to determine the capabilities of an on-linesensor 302. The sampling device 300 generates one or more simulationparameters 304 of a simulated sample texture. The simulated parameters304 may be properties of a typical texture examined by sensors 302. Thesimulation parameters 304 are fed into an analyzing device 306. Theanalyzing device 306 may feed the simulation parameters 304 into aqualitative comparator 308 and a quantitative comparator 310. Theanalysis performed by the qualitative comparator 308 and thequantitative comparator 310 is discussed later herein. The one or moresimulation parameters 304 are also fed into a computer algorithm 312.

The computer algorithm 312 may generate an image 314 similar to thatdiscussed with regard to the first exemplary sampling embodiment. Adisplay device 316 may be used to produce the image 314 on or into theon-line sensor 302. Similarly to the example discussed with regard tothe first exemplary sampling embodiment, the simulation parameters 304may be designed to take into account characteristics of the displaydevice 316. The displaying device 316 used to display may be a varietyof devices known to an individual skilled in the art. The device may beselected based on the on-line sensor 302 and characteristics of theimage 314. The display device 316 may use components and methods todisplay the image 314 in or onto the on-line sensor 302, for example,optical reflecting components, fiber optics, projection, and holograms.

The on-line sensor 302 scans the image 314 displayed. The on-line sensor302 or a component of the on-line sensor may separate the image 314viewed by the on-line sensor 302 into measured parameters 318. Themeasured parameters 318 are fed into the analyzing device 306. Theanalyzing device 306 may feed the measured parameters into thequalitative comparator 308 and the quantitative comparator 310. Thequalitative comparator 308 and the quantitative comparator 310 comparethe simulation parameters 304 to the measured parameters 318. Theanalyzing device 306 may provide an accurate comparison of the on-linesensor 302 to other sensors similar to the first exemplary samplingembodiment.

Referring to FIG. 4, a sampling device 400 according to a thirdexemplary sampling embodiment is used to evaluate a sensor. The samplingdevice 400 may be used to determine the capabilities of an on-linesensor 402. The sampling device 400 generates one or more assessedparameters 404 from an image of a sample texture by scientificinstrument, visual inspection, or a combination of both. The assessedparameters 404 may be determined by scanning a known sample using avariety of radiation sources, for example, light, x-ray, and electronbeam. The assessed parameters 404 may provide properties of a typicaltexture examined by sensors 402. The texture samples are selected sothat their assessment parameters can be determined by other knownaccurate methods, for example, visual inspection.

The assessed parameters 404 are fed into an analyzing device 406. Theanalyzing device 406 may feed the assessed parameters 404 into aqualitative comparator 408 and a quantitative comparator 410. Theanalysis performed by the qualitative comparator 408 and thequantitative comparator 410 is discussed later herein. The one or moreof the assessed parameters 404 are also fed into a computer algorithm412.

The computer algorithm 412 may generate an image 414 similar to thatdiscussed with regard to the first exemplary sampling embodiment. Theprocess of “generating” samples in this embodiment duplicates thetextures of the selected samples electronically. A printing device ordisplay device 416 may be used to produce the image 414 on or into theon-line sensor 402, as previously discussed with regard to the first andsecond exemplary sampling embodiments.

The on-line sensor 402 scans and separates the image 414 viewed by theon-line sensor 402 into measured parameters 418. The measured parameters418 are fed into the analyzing device 406. The analyzing device 406 mayfeed the measured parameters into the qualitative comparator 408 and thequantitative comparator 410. The qualitative comparator 408 and thequantitative comparator 410 compare the assessed parameters 404 to themeasured parameters 418. The analyzing device 406 may provide anaccurate comparison of the on-line sensor 402 to other sensors similarto the first exemplary sampling embodiment.

Referring to FIG. 5, a flow chart illustrates a first exemplary samplingmethod 500 embodiment of the present invention. The sampling processgenerates an image of a sample texture with known characteristics (block502). As previously discussed, the image may be produced usingsimulation parameters 204, 304 or assessed parameters 404. The image istransferred to an on-line sensor (block 504). This may be accomplishedwith a printing device 216 or a display device 316. The on-line sensorproduces measured parameters of the image (block 506). Analyzing device206, 306, 406 compares the measured characteristics to the knowncharacteristics (block 508). An accurate comparison of the on-linesensor 202, 302, 402 to other sensors may be provided as discussed withregard to the first exemplary sampling embodiment.

Referring to FIG. 6, a flow chart illustrates a second exemplarysampling method 600 embodiment of the present invention. The samplingprocess generates an image of a sample texture with knowncharacteristics (block 602). As previously discussed, the image may beproduced using simulation parameters 204, 304 or assessed parameters404. The image is transferred to an on-line sensor (block 604). This maybe accomplished with a printing device 216 or a display device 316. Theon-line sensor produces measured parameters of the image (block 606).The image is transferred to a laboratory sensor (block 608). This may beaccomplished with a printing device 216 or a display device 316. Thelaboratory sensor produces measured parameters of the image (block 610).An analyzing device 206 compares the known characteristics to themeasured characteristics of the on-line sensor and to the measuredcharacteristics of the laboratory sensor (block 612). The secondexemplary sampling method may be used to provide an accurate comparisonbetween a laboratory sensor and an on-line sensor.

It will be understood that the foregoing is only illustrative of theprinciples of the invention and that various modifications can be madeby those skilled in the art without departing from the scope and spiritof the invention. For example, the various embodiments described hereinmay comply with various known standards, for example, the TechnicalAssociation of the Pulp and Paper Industry (TAPPI) standards as well asother known industry and government standards. The sample texture maynot be limited to a web of paper.

Accordingly, such embodiments will be recognized as within the scope ofthe present invention. Persons skilled in the art will also appreciatethat the present invention can be practiced by other than the describedembodiments, which are presented for purposes of illustration ratherthan of limitation and that the present invention is limited only by theclaims that follow.

1. A method for determining one or more capabilities of an on-linesensor comprising: receiving, at the on-line sensor, light that hasinteracted with a product being produced by a production process;converting the received light into electrical signals; analyzing theelectrical signals to determine one or more characteristics of a textureof the product being produced; generating an image of a sample texture,the image providing a three-dimensional surface topography of anon-homogeneous medium, the image having one or more knowncharacteristics associated with the product being produced; transferringthe image to the on-line sensor; analyzing data generated by the on-linesensor to determine one or more on-line measured characteristics of theimage; transferring the image to a laboratory sensor; analyzing datagenerated by the laboratory sensor to determine one or more laboratorymeasured characteristics of the image; and comparing the one or moreknown characteristics of the image to the one or more on-line measuredcharacteristics of the image and to the one or more laboratory measuredcharacteristics of the image to determine which one of the laboratorysensor and the on-line sensor is more accurate, wherein the comparingcomprises both qualitative and quantitative comparisons.
 2. The methodof claim 1, wherein generating the image of the sample texture comprisesusing mathematical fractals to generate a two-dimensional matrix of adisordered medium.
 3. The method of claim 1, wherein generating theimage of the sample texture comprises generating a two-dimensionalmatrix of a disordered medium from an image of a known textured surface.4. The method of claim 1, wherein transferring the image comprisesprinting the image and presenting the printed image to the on-linesensor.
 5. The method of claim 1, wherein transferring the imagecomprises etching the image onto a medium and presenting the etchedmedium to the on-line sensor.
 6. The method of claim 1, whereintransferring the image comprises displaying the image and reflecting thedisplayed image onto the on-line sensor.
 7. The method of claim 1,wherein transferring the image to the on-line sensor comprises theon-line sensor scanning the image using one of an x-ray beam and anelectron beam.
 8. The method of claim 1, wherein generating the image ofthe sample texture comprises generating a two-dimensional matrix of adisordered medium from one or more mathematical formulas.
 9. The methodof claim 1, wherein comparing the one or more known characteristics tothe one or more on-line measured characteristics and to the one or morelaboratory measured characteristics of the image comprises generating amathematical formula of a cross-correlation between the one or moreon-line measured characteristics and the one or more knowncharacteristics and generating a mathematical formula of across-correlation between the one or more laboratory measuredcharacteristics and the one or more known characteristics.
 10. A devicefor determining one or more capabilities of an on-line sensor, thedevice comprising: a module configured to generate an image of a sampletexture, the image providing a three-dimensional surface topography of anon-homogeneous medium, the image having one or more knowncharacteristics associated with a product being produced by a productionprocess; a module configured to transfer the image to the on-linesensor, the on-line sensor configured to (i) receive light that hasinteracted with the product being produced by the production process,(ii) convert the received light into electrical signals, and (iii)provide the electrical signals for analysis to determine one or morecharacteristics of a texture of the product being produced; a moduleconfigured to analyze data generated by the on-line sensor based on theimage to determine one or more on-line measured characteristics of theimage; a module configured to transfer the image to a laboratory sensor;a module configured to analyze data generated by the laboratory sensorto determine one or more laboratory measured characteristics of theimage; and a module configured to qualitatively and quantitativelycompare the one or more known characteristics of the image to the one ormore on-line measured characteristics of the image and to the one ormore laboratory measured characteristics of the image to determine whichone of the laboratory sensor and the online sensor is more accurate, themodule comprising a qualitative comparator and a quantitativecomparator.
 11. The device of claim 10, wherein the module configured togenerate the image comprises a computer configured to generate atwo-dimensional matrix of a disordered medium.
 12. The device of claim10, wherein the module configured to transfer the image comprises aprinter configured to print the image for presentation to the on-linesensor.
 13. The device of claim 10, wherein the module configured totransfer the image comprises a display configured to display the imageto the on-line sensor.
 14. The device of claim 10, wherein the moduleconfigured to transfer the image comprises: a display configured todisplay the image; and an optical device configured to project thedisplayed image directly onto the on-line sensor.
 15. The device ofclaim 10, wherein the module configured to transfer the image to thelaboratory sensor is further configured to etch the image onto a mediumand present the etched medium to the on-line sensor.
 16. Anon-transitory machine-readable medium having instructions storedthereon for: generating an image of a sample texture, the imageproviding a three-dimensional surface topography of a non-homogeneousmedium, the image having one or more known characteristics associatedwith a product being produced by a production process; transferring theimage to an on-line sensor, the on-line sensor configured to (i) receivelight that has interacted with the product being produced by theproduction process, (ii) convert the received light into electricalsignals, and (iii) provide the electrical signals for analysis todetermine one or more characteristics of a texture of the product beingproduced; analyzing data generated by the on-line sensor based on theimage to determine one or more on-line measured characteristics of theimage; transferring the image to a laboratory sensor; analyzing datagenerated by the laboratory sensor to determine one or more laboratorymeasured characteristics of the image; and comparing the one or moreknown characteristics of the image to the one or more on-line measuredcharacteristics of the image and to the one or more laboratory measuredcharacteristics of the image to determine which one of the laboratorysensor and the online sensor is more accurate, wherein the comparingcomprises both qualitative and quantitative comparisons.
 17. Thenon-transitory machine-readable medium of claim 16, wherein theinstructions for generating the image of the sample texture compriseinstructions for generating a two-dimensional matrix of a disorderedmedium.
 18. The non-transitory machine-readable medium of claim 16,wherein the instructions for transferring the image compriseinstructions for displaying the image and for presenting the displayedimage to the on-line sensor.
 19. The non-transitory machine-readablemedium of claim 16, further comprising instructions for: etching theimage onto a medium; and presenting the etched medium to the on-linesensor.
 20. The non-transitory machine-readable medium of claim 16,wherein the instructions for comparing the one or more measuredcharacteristics to the one or more known characteristics compriseinstructions for generating a mathematical formula of across-correlation between the one or more measured characteristics andthe one or more known characteristics.
 21. The method of claim 1,wherein the image has one or more properties of a typical texture of theproduct being produced by the production process.